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Data & analytics / SQL analysis

SPARCS Healthcare SQL Insights

Use the right tool for the size of the question.

SQL and DuckDB analysis of over two million inpatient discharge records, focused on aggregate hospital, cost, and demographic patterns.

Data & analytics

Millions of records. Interpretable questions.

01Discharge records
02SQL preparation
03Group and aggregate
04Interpret patterns
01

The question

The SPARCS study examines hospital activity, efficiency, treatment costs, and demographic patterns across more than two million inpatient discharge records.

02

The approach

SQL queries clean, filter, group, and summarize inpatient records. DuckDB and Google Colab support the analytical workflow. Aggregation turns the raw records into hospital, cost, and demographic comparisons.

03

What it demonstrates

The project emphasizes scalable query-based analysis and careful grouping. Its outputs help describe patterns across populations and institutions, rather than focusing on individual patients.

04

Scope

This case study describes aggregate analysis, not clinical advice or patient-level decision making. No public interactive deployment is supplied, and individual discharge records are not reproduced in this portfolio.

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